ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2020
Selecting a Scale for Spatial Confounding Adjustment.
Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- Prenatal exposure to wildfire fine particulate matter and fetal growth outcomes in the United States: Findings from the ECHO Cohort.Environmental epidemiology (Philadelphia, Pa.) · 2026Article
- Bringing spatial confounding into the causal inferential fold.American journal of epidemiology · 2026Article
- Mitigating the risk of bias exacerbation when controlling for unmeasured spatial confounding for binary exposures.American journal of epidemiology · 2026Article
- Air Pollution and the Progression of Physical Function Limitations and Disability in Aging Adults.JAMA network open · 2026Article
- Air pollution predicts healthcare spending among older adults in the United States.Environment international · 2026Article
- Sharing common measures of the environment across continents: challenges and opportunities for global studies of aging.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026Article
- Particulate air pollution from different emission sources, cognitive performance, and cognitive declines in India.Environment international · 2025Article
- Semiparametric approaches for mitigating spatial confounding in large environmental epidemiology cohort studies.Environmetrics · 2025Article
- Consistency of common spatial estimators under spatial confounding.Biometrika · 2025Article
- Different types of greenspace within urban parks and depressive symptoms among older U.S. adults living in urban areas.Environment international · 2024Article
- Long-term air pollution exposure and incident physical disability in older US adults: a cohort study.The lancet. Healthy longevity · 2024Article
- Source-Specific Air Pollution and Loss of Independence in Older Adults Across the US.JAMA network open · 2024Article
- Residential greenspace and major depression among older adults living in urban and suburban areas with different climates across the United States.Environmental research · 2024Article
- Comparison ofEnvironmental health perspectives · 2024Article
- spconfShiny: An R Shiny application for calculating the spatial scale of smoothing splines for point data.PloS one · 2024Article
- Residential Structural Racism and Prevalence of Chronic Health Conditions.JAMA network open · 2023Article
- Spectral adjustment for spatial confounding.Biometrika · 2023Article
- Discussion on "Spatial+: A novel approach to spatial confounding" by Dupont, Wood, and Augustin.Biometrics · 2022Article
- Tracking the transmission dynamics of COVID-19 with a time-varying coefficient state-space model.Statistics in medicine · 2022Article
- Long-Term Ambient Air Pollution and Childhood Eczema in the United States.Environmental health perspectives · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Unmeasured, spatially-structured factors can confound associations between spatial environmental exposures and health outcomes. Adding flexible splines to a regression model is a simple approach for spatial confounding adjustment, but the spline degrees of freedom do not provide an easily interpretable spatial scale. We describe a method for quantifying the extent of spatial confounding adjustment in terms of the Euclidean distance at which variation is removed. We develop this approach for confounding adjustment with splines and using Fourier and wavelet filtering. We demonstrate differences in the spatial scales these bases can represent and provide a comparison of methods for selecting the amount of confounding adjustment. We find the best performance for selecting the amount of adjustment using an information criterion evaluated on an outcome model without exposure. We apply this method to spatial adjustment in an analysis of fine particulate matter and blood pressure in a cohort of United States women.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.